RankByGene: GeneGene-Guided Histopathology Representation Learning Through Cross-Modal Ranking Consistency [0.03%]
基于基因指导的跨模态排序一致性通过学习组织病理学表示_RANKBYGENE
Wentao Huang,Meilong Xu,Xiaoling Hu et al.
Wentao Huang et al.
Spatial transcriptomics (ST) provides essential spatial context by mapping gene expression within tissue, enabling detailed study of cellular heterogeneity and tissue organization. However, aligning ST data with histology images poses chall...
Comprehensive Analysis of Relative Pressure Estimation in Type B Aortic Dissection Utilizing 4D-Flow MRI [0.03%]
基于4D流MRI的B型主动脉夹层相对压力评估的全面分析
Brandon Hardy,Judith Zimmermann,Vincent Lechner et al.
Brandon Hardy et al.
Magnetic resonance imaging (MRI) can estimate three-dimensional (3D) time-resolved blood velocity fields using 4D-flow MRI, providing rich relative pressure field information. Clinical alternatives-catheterization and Doppler echocardiograp...
FreqPath-Net: Frequency-Aware Spectral-Orthogonal Network for Histopathological Nuclei Segmentation [0.03%]
频谱感知正交网络：具有频率意识的频谱正交网络用于组织病理学核分割
Jin Huang,Shengqian Wang,Wenchao Xue et al.
Jin Huang et al.
Nuclei segmentation is a fundamental but challenging task in computational pathology due to diverse morphologies, blurred boundaries, and staining variations. Despite remarkable progress, existing models often suffer from structural instabi...
Chuang Niu,Pengwei Wu,Bruno De Man et al.
Chuang Niu et al.
Foundation models (FMs) are rapidly reshaping medical imaging, shifting the field from narrowly trained, task-specific networks toward large, generalpurpose models that can be adapted across modalities, anatomies, and clinical tasks. In thi...
Yue Wang,Yuanbiao Yang,Zhuo-Xu Cui et al.
Yue Wang et al.
Magnetic Resonance Imaging (MRI) is an inherently multi-contrast modality, where cross-contrast priors can be exploited to improve image reconstruction from undersampled data. Recently, diffusion models have shown remarkable performance in ...
ToPPFed: Topological Prototype-Enhanced Personalized Federated Learning for Neuropsychiatric Disorders Identification [0.03%]
基于拓扑原型增强的个性化联邦学习的精神神经疾病识别方法
Yuxuan Zheng,Zifeng Jia,Zihao Guan et al.
Yuxuan Zheng et al.
Functional connectivity networks (FCNs) derived from functional magnetic resonance imaging (fMRI) have been widely used to characterize topological alterations of brain networks in neuropsychiatric disorders (NDs). Given the frequent restri...
Multi-Aspect Knowledge-Enhanced Dermatological Vision-Language Pretraining with Multi-Agent Data Generation [0.03%]
多方面知识增强的皮肤视觉语言预训练与多代理数据生成
Xieji Li,Siyuan Yan,Yingsheng Liu et al.
Xieji Li et al.
Vision-language pretraining (VLP) has emerged as a powerful paradigm in medical image analysis, enabling representation learning from large-scale image-text pairs without relying on expensive expertise annotations. However, these challenges...
Motion Artifact-Aware Self-Supervised Representation Learning for 3D Brain MRI Motion Artifact Reduction [0.03%]
一种用于减少3D脑MRI运动伪影的基于自监督学习的表示学习方法
Mojtaba Safari,Shansong Wang,Zach Eidex et al.
Mojtaba Safari et al.
Patient motion remains a source of image degradation in brain MRI, leading to signal loss, blurring, and geometric distortion that compromise quantitative analysis. Existing deep learning methods for motion correction typically rely on pair...
Endo-TTAP: Robust Endoscopic Tissue Tracking via Multi-Facet Guided Attention and Hybrid Flow-point Supervision [0.03%]
基于多导向注意力和混合流点监督的内窥镜组织跟踪方法
Rulin Zhou,Wenlong He,An Wang et al.
Rulin Zhou et al.
Accurate tissue point tracking in endoscopic videos is crucial for robotic-assisted surgical navigation and scene understanding, yet remains challenging due to complex tissue deformations, instrument occlusions, and the scarcity of dense tr...
SurgFusion-Net: Diversified Adaptive Multimodal Fusion Network for Surgical Skill Assessment [0.03%]
基于多样化的自适应多模态融合的手术技能评估网络
Runlong He,Freweini M Tesfai,Matthew W E Boal et al.
Runlong He et al.
Robotic-assisted surgery (RAS) is established in clinical practice, and automated surgical skill assessment utilizing multimodal data offers transformative potential for surgical analytics and education. However, developing effective multim...